/*

Copyright (C) 2001 Ross Lippert and Paul Kienzle

This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
02110-1301  USA

*/

#ifdef HAVE_CONFIG_H
#include <config.h>
#endif

#include <float.h>

#include "CmplxSCHUR.h"
#include "lo-ieee.h"
#include "lo-mappers.h"

#include "defun-dld.h"
#include "error.h"
#include "gripes.h"
#include "utils.h"

static inline double
getmin (double x, double y)
{
  return x < y ? x : y;
}

static inline double
getmax (double x, double y)
{
  return x > y ? x : y;
}

static double
frobnorm (const ComplexMatrix& A)
{
  double sum = 0;

  for (int i = 0; i < A.rows (); i++)
    for (int j = 0; j < A.columns (); j++)
      sum += real (A(i,j) * conj (A(i,j)));

  return sqrt (sum);
}

static double
frobnorm (const Matrix& A)
{
  double sum = 0;
  for (int i = 0; i < A.rows (); i++)
    for (int j = 0; j < A.columns (); j++)
      sum += A(i,j) * A(i,j);

  return sqrt (sum);
}


static ComplexMatrix
sqrtm_from_schur (const ComplexMatrix& U, const ComplexMatrix& T)
{
  const int n = U.rows ();

  ComplexMatrix R (n, n, 0.0);

  for (int j = 0; j < n; j++)
    R(j,j) = sqrt (T(j,j));

  const double fudge = sqrt (DBL_MIN);

  for (int p = 0; p < n-1; p++)
    {
      for (int i = 0; i < n-(p+1); i++)
	{
	  const int j = i + p + 1;

	  Complex s = T(i,j);

	  for (int k = i+1; k < j; k++)
	    s -= R(i,k) * R(k,j);

	  // dividing
	  //     R(i,j) = s/(R(i,i)+R(j,j));
	  // screwing around to not / 0

	  const Complex d = R(i,i) + R(j,j) + fudge;
	  const Complex conjd = conj (d);

	  R(i,j) =  (s*conjd)/(d*conjd);
	}
    }

  return U * R * U.hermitian ();
}

DEFUN_DLD (sqrtm, args, nargout,
 "-*- texinfo -*-\n\
@deftypefn {Loadable Function} {[@var{result}, @var{error_estimate}] =} sqrtm (@var{a})\n\
Compute the matrix square root of the square matrix @var{a}.\n\
\n\
Ref: Nicholas J. Higham. A new sqrtm for MATLAB. Numerical Analysis\n\
Report No. 336, Manchester Centre for Computational Mathematics,\n\
Manchester, England, January 1999.\n\
@end deftypefn\n\
@seealso{expm, logm, and funm}")
{
  octave_value_list retval;

  int nargin = args.length ();

  if (nargin != 1)
    {
      print_usage ("sqrtm");
      return retval;
    }

  octave_value arg = args(0);

  int n = arg.rows ();
  int nc = arg.columns ();

  int arg_is_empty = empty_arg ("sqrtm", n, nc);

  if (arg_is_empty < 0)
    return retval;
  else if (arg_is_empty > 0)
    return octave_value (Matrix ());

  if (n != nc)
    {
      gripe_square_matrix_required ("sqrtm");
      return retval;
    }

  retval(1) = lo_ieee_inf_value ();
  retval(0) = lo_ieee_nan_value ();

  if (arg.is_real_scalar ())
    {
      double d = arg.double_value ();
      if (d > 0.0)
	{
	  retval(0) = sqrt (d);
	  retval(1) = 0.0;
	}
      else
	{
	  retval(0) = Complex (0.0, sqrt (d));
	  retval(1) = 0.0;
	}
    }
  else if (arg.is_complex_scalar ())
    {
      Complex c = arg.complex_value ();
      retval(0) = sqrt (c);
      retval(1) = 0.0;
    }
  else if (arg.is_matrix_type ())
    {
      double err, minT;

      if (arg.is_real_matrix ())
	{
	  Matrix A = arg.matrix_value();

	  if (error_state)
	    return retval;

	  // XXX FIXME XXX -- eventually, ComplexSCHUR will accept a
	  // real matrix arg.

	  ComplexMatrix Ac (A);

	  const ComplexSCHUR schur (Ac, std::string ());

	  if (error_state)
	    return retval;

	  const ComplexMatrix U (schur.unitary_matrix ());
	  const ComplexMatrix T (schur.schur_matrix ());
	  const ComplexMatrix X (sqrtm_from_schur (U, T));

	  // Check for minimal imaginary part
	  double normX = 0.0;
	  double imagX = 0.0;
	  for (int i = 0; i < n; i++)
	    for (int j = 0; j < n; j++)
	      {
		imagX = getmax (imagX, imag (X(i,j)));
		normX = getmax (normX, abs (X(i,j)));
	      }

	  if (imagX < normX * 100 * DBL_EPSILON)
	    retval(0) = real (X);
	  else
	    retval(0) = X;

	  // Compute error
	  // XXX FIXME XXX can we estimate the error without doing the
	  // matrix multiply?

	  err = frobnorm (X*X - ComplexMatrix (A)) / frobnorm (A);

	  if (xisnan (err))
	    err = lo_ieee_inf_value ();

	  // Find min diagonal
	  minT = lo_ieee_inf_value ();
	  for (int i=0; i < n; i++)
	    minT = getmin(minT, abs(T(i,i)));
	}
      else
	{
	  ComplexMatrix A = arg.complex_matrix_value ();

	  if (error_state)
	    return retval;

	  const ComplexSCHUR schur (A, std::string ());

	  if (error_state)
	    return retval;

	  const ComplexMatrix U (schur.unitary_matrix ());
	  const ComplexMatrix T (schur.schur_matrix ());
	  const ComplexMatrix X (sqrtm_from_schur (U, T));

	  retval(0) = X;

	  err = frobnorm (X*X - A) / frobnorm (A);

	  if (xisnan (err))
	    err = lo_ieee_inf_value ();

	  minT = lo_ieee_inf_value ();
	  for (int i = 0; i < n; i++)
	    minT = getmin (minT, abs (T(i,i)));
	}

      retval(1) = err;

      if (nargout < 2)
	{
	  if (err > 100*(minT+DBL_EPSILON)*n)
	    {
	      if (minT == 0.0)
		error ("sqrtm: A is singular, sqrt may not exist");
	      else if (minT <= sqrt (DBL_MIN))
		error ("sqrtm: A is nearly singular, failed to find sqrt");
	      else
		error ("sqrtm: failed to find sqrt");
	    }
	}
    }
  else
    gripe_wrong_type_arg ("sqrtm", arg);

  return retval;
}

/*
;;; Local Variables: ***
;;; mode: C++ ***
;;; End: ***
*/
